Triplet attention-enhanced residual tree-inspired decision network: A hierarchical fault diagnosis model for unbalanced bearing datasets
In fault classification tasks, deep neural networks (DNNs) have remarkable recognition
performance. Nevertheless, the classification decision processes of DNNs lack hierarchical …
performance. Nevertheless, the classification decision processes of DNNs lack hierarchical …
Digital twin-driven graph domain adaptation neural network for remaining useful life prediction of rolling bearing
L Cui, Y Xiao, D Liu, H Han - Reliability Engineering & System Safety, 2024 - Elsevier
Remaining useful life (RUL) prediction is significant for the healthy operation of machinery.
In order to accurately identify the bearing degeneration states, it is necessary to collect …
In order to accurately identify the bearing degeneration states, it is necessary to collect …
A novel adaptive generalized domain data fusion-driven kernel sparse representation classification method for intelligent bearing fault diagnosis
L Cui, Z Jiang, D Liu, H Wang - Expert Systems with Applications, 2024 - Elsevier
Dictionary learning has gradually attracted attention due to its powerful feature
representation ability. However, the time-shift property of collected signals hinders the …
representation ability. However, the time-shift property of collected signals hinders the …
An intelligent bearing fault diagnosis framework: one-dimensional improved self-attention-enhanced CNN and empirical wavelet transform
The complexity of the internal structure of rolling bearings and the harshness of their
operating environment result in strong non-stationarity and nonlinearity of the vibration …
operating environment result in strong non-stationarity and nonlinearity of the vibration …
A novel robust dual unscented particle filter method for remaining useful life prediction of rolling bearings
L Cui, W Li, D Liu, H Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
It is still challenging to accurately predict the remaining useful life (RUL) of bearings with
fluctuating degradation processes. To address this issue, this article proposes a novel robust …
fluctuating degradation processes. To address this issue, this article proposes a novel robust …
A spectral coherence cyclic periodic index optimization-gram for bearing fault diagnosis
L Cui, X Zhao, D Liu, H Wang - Measurement, 2024 - Elsevier
The identification of optimal frequency band (OFB) sensitive to faults is crucial for bearing
fault diagnosis. In this paper, a spectral coherence cyclic periodic index (SCCP) optimization …
fault diagnosis. In this paper, a spectral coherence cyclic periodic index (SCCP) optimization …
Advancing RUL prediction in mechanical systems: A hybrid deep learning approach utilizing non-full lifecycle data
T Lin, L Song, L Cui, H Wang - Advanced Engineering Informatics, 2024 - Elsevier
This paper addresses the significant challenge of predicting the Remaining Useful Life
(RUL) of mechanical equipment, a critical aspect of predictive maintenance and reliability …
(RUL) of mechanical equipment, a critical aspect of predictive maintenance and reliability …
Counterfactual-augmented few-shot contrastive learning for machinery intelligent fault diagnosis with limited samples
Capturing sufficient and balanced data for intelligent fault diagnosis is significantly
consumptive in practice. It is tricky and demand-oriented to identify faults accurately and …
consumptive in practice. It is tricky and demand-oriented to identify faults accurately and …
Interpretable domain adaptation transformer: a transfer learning method for fault diagnosis of rotating machinery
D Liu, L Cui, G Wang, W Cheng - Structural Health …, 2024 - journals.sagepub.com
Domain adaptation-based transfer learning methods have been widely investigated in fault
diagnosis of rotating machinery, but their basic convolution or recurrent structure is subject …
diagnosis of rotating machinery, but their basic convolution or recurrent structure is subject …
A new multiple mixed augmentation-based transfer learning method for machinery fault diagnosis
H Ge, C Shen, X Lin, D Wang, J Shi… - Measurement …, 2024 - iopscience.iop.org
With the continuous development of various industries, the diagnosis of industrial equipment
faults has been receiving increasing attention in recent years. Considering the complex and …
faults has been receiving increasing attention in recent years. Considering the complex and …